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<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Dear Makato,<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">This depends on the connectivity measure that you wish to apply.<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Phase dependent measures or cross-frequency measures are strongly influenced by filter settings<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">If you use those than stay away from your sampling rate<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">The 1/3 or ¼ of the sampling frequency as a limit –in stead of the Nyquist criterium- is more safe<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D"><o:p> </o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Regards<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US" style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1F497D">Bob van Dijk<o:p></o:p></span></p>
<p class="MsoNormal"><span lang="EN-US"><o:p> </o:p></span></p>
<p class="MsoNormal"><b><span style="font-size:10.0pt;font-family:"Tahoma","sans-serif"">Van:</span></b><span style="font-size:10.0pt;font-family:"Tahoma","sans-serif""> eeglablist-bounces@sccn.ucsd.edu [mailto:eeglablist-bounces@sccn.ucsd.edu]
<b>Namens </b>Makoto Miyakoshi<br>
<b>Verzonden:</b> dinsdag 23 juni 2015 23:07<br>
<b>Aan:</b> Vito De Feo<br>
<b>CC:</b> EEGLAB List<br>
<b>Onderwerp:</b> Re: [Eeglablist] Effect of anti-aliasing low-pass filter on connectivity analysis<o:p></o:p></span></p>
<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Thank you Vito for your response. Forgive me to ask you one more question.<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">As the ERP handbook by Luck (or his other book) recommends, anti-aliasing should better have the margin of 4-5 times of the new sampling rate e.g. if you downsample signlas to 250 Hz, anti-aliasing low-pass at 125 Hz is the standard, but
recommendation is 75 Hz or even 50 Hz. Well, I haven't tested it myself so I am not sure what bad it would do if I use 125 Hz (any comment on this, anyone?) but in this case, I guess the anti-aliasing low-pass filter does affect the subsequest connectivity
analysis--am I correct (assuming that I analyze EEG up to 50 Hz)?<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">Makoto<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">On Mon, Jun 22, 2015 at 9:31 AM, Vito De Feo <<a href="mailto:vito.defeo@zmnh.uni-hamburg.de" target="_blank">vito.defeo@zmnh.uni-hamburg.de</a>> wrote:<o:p></o:p></p>
<p class="MsoNormal">Dear Makoto,<br>
this will not affect the connectivity analysis if the frequency of interest are far from the Nyquist frequency. For example if you downsample to 500 Hz (Nyquist freq = 250 Hz) you will have no problem in the band 0-100 Hz.<br>
Best<br>
Vito<o:p></o:p></p>
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<p class="MsoNormal"><br>
Il giorno 20/giu/2015, alle ore 00:28, Makoto Miyakoshi ha scritto:<br>
<br>
> Dear List,<br>
><br>
> If I use zero-phase low-pass filter for anti-aliasing, does it affect the subsequent connectivity analysis? I ask this because EEGLAB pop_resample() automatically applies it. If it does, is there a workaround? Should I use minimum phase causal filter for
anti-aliasing?<br>
><br>
> --<br>
> Makoto Miyakoshi<br>
> Swartz Center for Computational Neuroscience<br>
> Institute for Neural Computation, University of California San Diego<o:p></o:p></p>
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<p class="MsoNormal"><span class="hoenzb"><span style="color:#888888">--</span></span><span style="color:#888888"><br>
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<o:p></o:p></p>
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<p class="MsoNormal"><o:p> </o:p></p>
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<p class="MsoNormal">-- <o:p></o:p></p>
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<p class="MsoNormal">Makoto Miyakoshi<br>
Swartz Center for Computational Neuroscience<br>
Institute for Neural Computation, University of California San Diego<o:p></o:p></p>
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